metadata

language:
  - gl
license: apache-2.0
base_model: openai/whisper-large
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Large Galician
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0 gl
          type: mozilla-foundation/common_voice_13_0
          config: gl
          split: test
          args: gl
        metrics:
          - name: Wer
            type: wer
            value: 6.939845474613686

Whisper Large Galician

This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common_voice_13_0 gl dataset. It achieves the following results on the evaluation set:

Loss: 0.3605
Wer: 6.9398

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 20000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0126	4.01	1000	0.2128	8.3558
0.0032	9.01	2000	0.2262	6.9416
0.0022	14.01	3000	0.2528	7.1123
0.0025	19.01	4000	0.2643	7.3641
0.0015	24.01	5000	0.2596	7.3365
0.0014	29.01	6000	0.2723	7.6366
0.0008	34.01	7000	0.2778	7.6090
0.0003	39.01	8000	0.2880	7.2261
0.0004	44.01	9000	0.2920	7.6745
0.0001	49.01	10000	0.2854	7.4089
0.0	54.01	11000	0.3027	7.4365
0.0	59.01	12000	0.3159	7.4055
0.0	64.01	13000	0.3242	7.3693
0.0	69.01	14000	0.3312	7.3072
0.0	74.01	15000	0.3379	7.0226
0.0	79.01	16000	0.3442	7.0019
0.0	84.01	17000	0.3500	6.9933
0.0	89.01	18000	0.3550	6.9605
0.0	94.01	19000	0.3589	6.9467
0.0	99.01	20000	0.3605	6.9398

Framework versions

Transformers 4.33.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3

Citation

If you use these models in your research, please cite:

@misc{dezuazo2025whisperlmimprovingasrmodels,
      title={Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languages}, 
      author={Xabier de Zuazo and Eva Navas and Ibon Saratxaga and Inma Hernáez Rioja},
      year={2025},
      eprint={2503.23542},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2503.23542}, 
}

Please, check the related paper preprint in arXiv:2503.23542 for more details.

Licensing

This model is available under the Apache-2.0 License. You are free to use, modify, and distribute this model as long as you credit the original creators.